The Mps1 Kinase Modulates the Recruitment and Activity of Cnn1CENP-T at Saccharomyces cerevisiae Kinetochores

Kinetochores are conserved protein complexes that bind the replicated chromosomes to the mitotic spindle and then direct their segregation. To better comprehend Saccharomyces cerevisiae kinetochore function, we dissected the phospho-regulated dynamic interaction between conserved kinetochore protein Cnn1^CENP-T, the centromere region, and the Ndc80 complex through the cell cycle. Cnn1 localizes to kinetochores at basal levels from G1 through metaphase but accumulates abruptly at anaphase onset. How Cnn1 is recruited and which activities regulate its dynamic localization are unclear. We show that Cnn1 harbors two kinetochore-localization activities: a C-terminal histone-fold domain (HFD) that associates with the centromere region and a N-terminal Spc24/Spc25 interaction sequence that mediates linkage to the microtubule-binding Ndc80 complex. We demonstrate that the established Ndc80 binding site in the N terminus of Cnn1, Cnn1^60–84, should be extended with flanking residues, Cnn1^25–91, to allow near maximal binding affinity to Ndc80. Cnn1 localization was proposed to depend on Mps1 kinase activity at Cnn1–S74, based on in vitro experiments demonstrating the Cnn1–Ndc80 complex interaction. We demonstrate that from G1 through metaphase, Cnn1 localizes via both its HFD and N-terminal Spc24/Spc25 interaction sequence, and deletion or mutation of either region results in anomalous Cnn1 kinetochore levels. At anaphase onset (when Mps1 activity decreases) Cnn1 becomes enriched mainly via the N-terminal Spc24/Spc25 interaction sequence. In sum, we provide the first in vivo evidence of Cnn1 preanaphase linkages with the kinetochore and enrichment of the linkages during anaphase.     

New Regulators of Clathrin-Mediated Endocytosis Identified in Saccharomyces cerevisiae by Systematic Quantitative Fluorescence Microscopy

Despite the importance of clathrin-mediated endocytosis (CME) for cell biology, it is unclear if all components of the machinery have been discovered and many regulatory aspects remain poorly understood. Here, using Saccharomyces cerevisiae and a fluorescence microscopy screening approach we identify previously unknown regulatory factors of the endocytic machinery. We further studied the top scoring protein identified in the screen, Ubx3, a member of the conserved ubiquitin regulatory X (UBX) protein family. In vivo and in vitro approaches demonstrate that Ubx3 is a new coat component. Ubx3-GFP has typical endocytic coat protein dynamics with a patch lifetime of 45 ± 3 sec. Ubx3 contains a W-box that mediates physical interaction with clathrin and Ubx3-GFP patch lifetime depends on clathrin. Deletion of the UBX3 gene caused defects in the uptake of Lucifer Yellow and the methionine transporter Mup1 demonstrating that Ubx3 is needed for efficient endocytosis. Further, the UBX domain is required both for localization and function of Ubx3 at endocytic sites. Mechanistically, Ubx3 regulates dynamics and patch lifetime of the early arriving protein Ede1 but not later arriving coat proteins or actin assembly. Conversely, Ede1 regulates the patch lifetime of Ubx3. Ubx3 likely regulates CME via the AAA-ATPase Cdc48, a ubiquitin-editing complex. Our results uncovered new components of the CME machinery that regulate this fundamental process.     

Redundant Regulation of Cdk1 Tyrosine Dephosphorylation in Saccharomyces cerevisiae

Cdk1 activity drives both mitotic entry and the metaphase-to-anaphase transition in all eukaryotes. The kinase Wee1 and the phosphatase Cdc25 regulate the mitotic activity of Cdk1 by the reversible phosphorylation of a conserved tyrosine residue. Mutation of cdc25 in Schizosaccharomyces pombe blocks Cdk1 dephosphorylation and causes cell cycle arrest. In contrast, deletion of MIH1, the cdc25 homolog in Saccharomyces cerevisiae, is viable. Although Cdk1-Y19 phosphorylation is elevated during mitosis in mih1∆ cells, Cdk1 is dephosphorylated as cells progress into G₁, suggesting that additional phosphatases regulate Cdk1 dephosphorylation. Here we show that the phosphatase Ptp1 also regulates Cdk1 dephosphorylation in vivo and can directly dephosphorylate Cdk1 in vitro. Using a novel in vivo phosphatase assay, we also show that PP2A bound to Rts1, the budding yeast B56-regulatory subunit, regulates dephosphorylation of Cdk1 independently of a function regulating Swe1, Mih1, or Ptp1, suggesting that PP2A^Rts1 either directly dephosphorylates Cdk1-Y19 or regulates an unidentified phosphatase.     

Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

Evolving Digital Ecological Networks

“It is hard to realize that the living world as we know it is just one among many possibilities” [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

This is a “Topic Page” article for PLOS Computational Biology.

     

Compression of FASTQ and SAM Format Sequencing Data

Storage and transmission of the data produced by modern DNA sequencing instruments has become a major concern, which prompted the Pistoia Alliance to pose the SequenceSqueeze contest for compression of FASTQ files. We present several compression entries from the competition, Fastqz and Samcomp/Fqzcomp, including the winning entry. These are compared against existing algorithms for both reference based compression (CRAM, Goby) and non-reference based compression (DSRC, BAM) and other recently published competition entries (Quip, SCALCE). The tools are shown to be the new Pareto frontier for FASTQ compression, offering state of the art ratios at affordable CPU costs. All programs are freely available on SourceForge. Fastqz: https://sourceforge.net/projects/fastqz/, fqzcomp: https://sourceforge.net/projects/fqzcomp/, and samcomp: https://sourceforge.net/projects/samcomp/.     

Viral Phylodynamics

Viral phylodynamics is defined as the study of how epidemiological, immunological, and evolutionary processes act and potentially interact to shape viral phylogenies. Since the coining of the term in 2004, research on viral phylodynamics has focused on transmission dynamics in an effort to shed light on how these dynamics impact viral genetic variation. Transmission dynamics can be considered at the level of cells within an infected host, individual hosts within a population, or entire populations of hosts. Many viruses, especially RNA viruses, rapidly accumulate genetic variation because of short generation times and high mutation rates. Patterns of viral genetic variation are therefore heavily influenced by how quickly transmission occurs and by which entities transmit to one another. Patterns of viral genetic variation will also be affected by selection acting on viral phenotypes. Although viruses can differ with respect to many phenotypes, phylodynamic studies have to date tended to focus on a limited number of viral phenotypes. These include virulence phenotypes, phenotypes associated with viral transmissibility, cell or tissue tropism phenotypes, and antigenic phenotypes that can facilitate escape from host immunity. Due to the impact that transmission dynamics and selection can have on viral genetic variation, viral phylogenies can therefore be used to investigate important epidemiological, immunological, and evolutionary processes, such as epidemic spread [2], spatio-temporal dynamics including metapopulation dynamics [3], zoonotic transmission, tissue tropism [4], and antigenic drift [5]. The quantitative investigation of these processes through the consideration of viral phylogenies is the central aim of viral phylodynamics.

This is a “Topic Page” article for PLOS Computational Biology.

     

Asymmetric Wnt Pathway Signaling Facilitates Stem Cell-Like Divisions via the Nonreceptor Tyrosine Kinase FRK-1 in Caenorhabditis elegans

Asymmetric cell division is critical during development, as it influences processes such as cell fate specification and cell migration. We have characterized FRK-1, a homolog of the mammalian Fer nonreceptor tyrosine kinase, and found it to be required for differentiation and maintenance of epithelial cell types, including the stem cell-like seam cells of the hypodermis. A genomic knockout of frk-1, allele ok760, results in severely uncoordinated larvae that arrest at the L1 stage and have an excess number of lateral hypodermal cells that appear to have lost asymmetry in the stem cell-like divisions of the seam cell lineage. frk-1(ok760) mutants show that there are excess lateral hypodermal cells that are abnormally shaped and smaller in size compared to wild type, a defect that could be rescued only in a manner dependent on the kinase activity of FRK-1. Additionally, we observed a significant change in the expression of heterochronic regulators in frk-1(ok760) mutants. However, frk-1(ok760) mutants do not express late, nonseam hypodermal GFP markers, suggesting the seam cells do not precociously differentiate as adult-hyp7 cells. Finally, our data also demonstrate a clear role for FRK-1 in seam cell proliferation, as eliminating FRK-1 during the L3–L4 transition results in supernumerary seam cell nuclei that are dependent on asymmetric Wnt signaling. Specifically, we observe aberrant POP-1 and WRM-1 localization that is dependent on the presence of FRK-1 and APR-1. Overall, our data suggest a requirement for FRK-1 in maintaining the identity and proliferation of seam cells primarily through an interaction with the asymmetric Wnt pathway.     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

This is a “Topic Page” article for PLOS Computational Biology.

     

Genome sequence of the moderately halophilic bacterium Salinicoccus carnicancri type strain CrmT (= DSM 23852T)

Salinicoccus carnicancri Jung et al. 2010 belongs to the genus Salinicoccus in the family Staphylococcaceae. Members of the Salinicoccus are moderately halophilic and originate from various salty environments. The halophilic features of the Salinicoccus suggest their possible uses in biotechnological applications, such as biodegradation and fermented food production. However, the genus Salinicoccus is poorly characterized at the genome level, despite its potential importance. This study presents the draft genome sequence of S. carnicancri strain Crm^T and its annotation. The 2,673,309 base pair genome contained 2,700 protein-coding genes and 78 RNA genes with an average G+C content of 47.93 mol%. It was notable that the strain carried 72 predicted genes associated with osmoregulation, which suggests the presence of beneficial functions that facilitate growth in high-salt environments.     

Genome sequence of the reddish-pigmented Rubellimicrobium thermophilum type strain (DSM 16684T), a member of the Roseobacter clade

Rubellimicrobium thermophilum Denner et al. 2006 is the type species of the genus Rubellimicrobium, a representative of the Roseobacter clade within the Rhodobacteraceae. Members of this clade were shown to be abundant especially in coastal and polar waters, but were also found in microbial mats and sediments. They are metabolically versatile and form a physiologically heterogeneous group within the Alphaproteobacteria. Strain C-Ivk-R2A-2^T was isolated from colored deposits in a pulp dryer; however, its natural habitat is so far unknown. Here we describe the features of this organism, together with the draft genome sequence and annotation and novel aspects of its phenotype. The 3,161,245 bp long genome contains 3,243 protein-coding and 45 RNA genes.     

The Genomic Blueprint of Salmonella enterica subspecies enterica serovar Typhi P-stx-12

Salmonella enterica subspecies enterica serovar Typhi is a rod-shaped, Gram-negative, facultatively anaerobic bacterium. It belongs to the family Enterobacteriaceae in the class Gammaproteobacteria, and has the capability of residing in the human gallbladder by forming a biofilm and hence causing the person to become a typhoid carrier. Here we present the complete genome of Salmonella enterica subspecies enterica serotype Typhi strain P-stx-12, which was isolated from a chronic carrier in Varanasi, India. The complete genome comprises a 4,768,352 bp chromosome with a total of 98 RNA genes, 4,691 protein-coding genes and a 181,431 bp plasmid. Genome analysis revealed that the organism is closely related to Salmonella enterica serovar Typhi strain Ty2 and Salmonella enterica serovar Typhi strain CT18, although their genome structure is slightly different.     

Hedgehog Signaling Strength Is Orchestrated by the mir-310 Cluster of MicroRNAs in Response to Diet

Since the discovery of microRNAs (miRNAs) only two decades ago, they have emerged as an essential component of the gene regulatory machinery. miRNAs have seemingly paradoxical features: a single miRNA is able to simultaneously target hundreds of genes, while its presence is mostly dispensable for animal viability under normal conditions. It is known that miRNAs act as stress response factors; however, it remains challenging to determine their relevant targets and the conditions under which they function. To address this challenge, we propose a new workflow for miRNA function analysis, by which we found that the evolutionarily young miRNA family, the mir-310s (mir-310/mir-311/mir-312/mir-313), are important regulators of Drosophila metabolic status. mir-310s-deficient animals have an abnormal diet-dependent expression profile for numerous diet-sensitive components, accumulate fats, and show various physiological defects. We found that the mir-310s simultaneously repress the production of several regulatory factors (Rab23, DHR96, and Ttk) of the evolutionarily conserved Hedgehog (Hh) pathway to sharpen dietary response. As the mir-310s expression is highly dynamic and nutrition sensitive, this signal relay model helps to explain the molecular mechanism governing quick and robust Hh signaling responses to nutritional changes. Additionally, we discovered a new component of the Hh signaling pathway in Drosophila, Rab23, which cell autonomously regulates Hh ligand trafficking in the germline stem cell niche. How organisms adjust to dietary fluctuations to sustain healthy homeostasis is an intriguing research topic. These data are the first to report that miRNAs can act as executives that transduce nutritional signals to an essential signaling pathway. This suggests miRNAs as plausible therapeutic agents that can be used in combination with low calorie and cholesterol diets to manage quick and precise tissue-specific responses to nutritional changes.     

The NuA4 Complex Promotes Translesion Synthesis (TLS)-Mediated DNA Damage Tolerance

Lesions in DNA can block replication fork progression, leading to its collapse and gross chromosomal rearrangements. To circumvent such outcomes, the DNA damage tolerance (DDT) pathway becomes engaged, allowing the replisome to bypass a lesion and complete S phase. Chromatin remodeling complexes have been implicated in the DDT pathways, and here we identify the NuA4 remodeler, which is a histone acetyltransferase, to function on the translesion synthesis (TLS) branch of DDT. Genetic analyses in Saccharomyces cerevisiae showed synergistic sensitivity to MMS when NuA4 alleles, esa1-L254P and yng2Δ, were combined with the error-free bypass mutant ubc13Δ. The loss of viability was less pronounced when NuA4 complex mutants were disrupted in combination with error-prone/TLS factors, such as rev3Δ, suggesting an epistatic relationship between NuA4 and error-prone bypass. Consistent with cellular viability measurements, replication profiles after exposure to MMS indicated that small regions of unreplicated DNA or damage were present to a greater extent in esa1-L254P/ubc13Δ mutants, which persist beyond the completion of bulk replication compared to esa1-L254P/rev3Δ. The critical role of NuA4 in error-prone bypass is functional even after the bulk of replication is complete. Underscoring this observation, when Yng2 expression is restricted specifically to G2/M of the cell cycle, viability and TLS-dependent mutagenesis rates were restored. Lastly, disruption of HTZ1, which is a target of NuA4, also resulted in mutagenic rates of reversion on level with esa1-L254P and yng2Δ mutants, indicating that the histone variant H2A.Z functions in vivo on the TLS branch of DDT.     

Non-contiguous finished genome sequence and description of Holdemania massiliensis sp. nov.

Holdemania massiliensis strain AP2^T sp. nov. is the type strain of H. massiliensis sp. nov., a new species within the genus Holdemania. This strain, whose genome is described here, was isolated from the fecal flora of a 21-year-old French Caucasian female suffering from severe restrictive anorexia nervosa. H. massiliensis is a Gram-positive, anaerobic bacillus. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 3,795,625 bp-long genome (one chromosome but no plasmid) contains 3,461 protein-coding and 49 RNA genes, including 3 rRNA genes.